Publications associées à Complex-Valued-Autoencoder for Structural Health Monitoring with Frequency Modulated Continuous Wave Radar

Non-contact sensing for anomaly detection in wind turbine blades: A focus-SVDD with complex-valued auto-encoder approach

The occurrence of manufacturing defects in wind turbine blade (WTB) production can result in significant increases in operation and maintenance costs of WTBs, reduce capacity factors of wind farms, and occasionally lead to severe and disastrous consequence ...

2024

A 0.14-nJ/b 200-Mb/s 2.7-3.5-GHz Quasi-Balanced FSK Transceiver With PLL-Based Modulation and Sideband Energy Detection

Cong Ding, Bowen Wang

This paper describes a balanced frequency shift keying (FSK) modulation, namely quasi-balanced FSK (QB-FSK), for energy-efficient high-data-rate communication. Not suffering from data-pattern dependency, the proposed modulation method enables frequency mod ...

2024

Towards an improved understanding of wind turbine wakes in complex terrain

Arslan Salim Dar

In this thesis, we explored the effect of certain terrain-induced flow phenomena on the development of wind turbines sited in complex terrain. A combined experimental and analytical approach is used to study wind turbine wakes in different types of complex ...

EPFL2024

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Pakshal Narendra Bohra

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

EPFL2024

Optimal blade pitch control for enhanced vertical-axis wind turbine performance

Sébastien Le Fouest, Karen Ann J Mulleners

Vertical-axis wind turbines are great candidates to enable wind power extraction in urban and off-shore applications. Currently, concerns around turbine efficiency and structural integrity limit their industrial deployment. Flow control can mitigate these ...

Nature Research2024

Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades

Véronique Michaud, Anastasios Vassilopoulos, Jialiang Fan

This article investigates the effects of voids, joint geometry, and test conditions on the quasi-static Mode I fracture performance of thick adhesive Double Cantilever Beam (DCB) joints such as those prevailing in wind industry and shipbuilding. The specim ...

2024

The effect of nacelle-to-rotor size on the wake of a miniature wind turbine

Fernando Porté Agel, Arslan Salim Dar, Rim Majzoub

Wind tunnel experiments are performed to investigate the effect of nacelle-to-rotor size on the wake of a wind turbine under different Reynolds numbers. Four different turbine configurations are tested, which vary in the rotor diameter and nacelle length a ...

IOP Science2024

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Jan Sickmann Hesthaven, Federico Pichi

The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling (ROM) context, one is interested in obtaining real -time and many-query evaluations of parametric ...

Academic Press Inc Elsevier Science2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Michele Bianco, Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Safe Deep Neural Networks

Kyle Michael Matoba

The capabilities of deep learning systems have advanced much faster than our ability to understand them. Whilst the gains from deep neural networks (DNNs) are significant, they are accompanied by a growing risk and gravity of a bad outcome. This is troubli ...

EPFL2024

Aggregating Spatial and Photometric Context for Photometric Stereo

David Honzátko

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

Enhancing Wind Farm Performance through Axial Induction and Tilt Control: Insights from Wind Tunnel Experiments

Fernando Porté Agel, Guillem Armengol Barcos

Static axial induction control and tilt control are two strategies that have the potential to increase power production in wind farms, mitigating wake effects and increasing the available power for downstream turbines. In this study, wind tunnel experiment ...

MDPI2024

Wind turbine wake superposition under pressure gradient

Fernando Porté Agel, Arslan Salim Dar

We investigate the effect of pressure gradient on the cumulative wake of multiple turbines in wind tunnel experiments spanning across a range of adverse pressure gradient (APG), zero pressure gradient (ZPG), and favorable pressure gradient (FPG). Compared ...

2024

Ultra-Low Power Short-Range 60-GHz FMCW Radar Front-End

Sammy Cerida Rengifo

The millimeter wave (mmWave) frequency band is becoming very interesting over the past years because it provides the opportunity to operate using large bandwidths which are not available at lower frequencies. This enables new communication standards suppor ...

EPFL2023

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Alexis Berne, Gionata Ghiggi, Anne-Claire Marie Billault--Roux

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

COPERNICUS GESELLSCHAFT MBH2023

Backpropagation-free training of deep physical neural networks

Romain Christophe Rémy Fleury, Babak Rahmani, Ali Momeni, Marc Philipp Del Hougne, Matthieu Francis Malléjac

Recent successes in deep learning for vision and natural language processing are attributed to larger models but come with energy consumption and scalability issues. Current training of digital deep-learning models primarily relies on backpropagation that ...

American Association for the Advancement of Science2023

Programmable Silicon Nitride Photonic Integrated Circuits

Rui Ning Wang, Tobias Kippenberg, Andrey Voloshin, Anat Siddharth, Viacheslav Snigirev, Andrea Bancora, Vladimir Shadymov

Silicon Nitride (Si3N4) photonic integrated circuits (PICs) have emerged as core technology in a variety of applications ranging from LIDAR to quantum control and computing. However, the need for high-speed, low-voltage tuning and modulation has been a lon ...

IEEE2023

Dynamic stall characterisation and control for vertical-axis wind turbines

Sébastien Le Fouest

According to the International Energy Agency, the global net-zero emissions objective requires the installed wind power capacity to increase 11-fold between 2020 and 2050. The scientific community has recently voiced concerns about the logistic feasibility ...

EPFL2023

Fatigue behavior and life prediction of wind turbine blade composite materials

Anastasios Vassilopoulos

Fatigue life prediction of wind turbine rotor blades is a very challenging task, as their failure is led by different failure types that act synergistically. Inherent defects like wrinkles, fiber misalignments, and voids that can be introduced during fabri ...

Woodhead Publishing (Elsevier)2023

Time scales of dynamic stall development on a vertical-axis wind turbine blade

Sébastien Le Fouest, Karen Ann J Mulleners, Daniel Marie Fernex

Vertical-axis wind turbines are excellent candidates to diversify wind energy technology, but their aerodynamic complexity limits industrial deployment. To improve the efficiency and lifespan of vertical-axis wind turbines, we desire data-driven models and ...

2023